




Summary: Finastra is seeking an AI Platform Engineer to productionize ML and AI systems, focusing on agentic workflows within core banking products, sitting at the intersection of platform engineering, MLOps, LLMOps, and application runtime. Highlights: 1. Build and operate production MLOps and LLMOps workflows 2. Design CI/CD pipelines for AI systems and implement observability 3. Shape the future of financial services software with AI innovation **Who are we?** =============== At Finastra, we’re a global leader in financial services software, dedicated to expanding access to financial services and shaping what’s next for the industry. Our technology powers mission‑critical solutions across Lending, Payments and Universal Banking, supporting over 7,000 customers, including 80% of the world’s top 50 banks, in more than 110 countries. **Role overview** ----------------- We are hiring an AI Platform Engineer to productionise ML and AI systems across our core banking products, with a particular focus on agentic workflows. This role sits at the point where platform engineering, MLOps, LLMOps, and application runtime meet. You will build the deployment, orchestration, observability, and control layers needed to run production AI systems safely and reliably. That includes predictive ML models, retrieval\-based systems, and agentic workflows that use tools, APIs, memory, and multi\-step orchestration in enterprise environments. You will help move us from isolated proofs of concept to repeatable production patterns that work in a regulated banking context. **What you do** --------------- * Build and operate production MLOps and LLMOps workflows across development, test, and production environments. * Create deployment patterns for ML models, LLM\-powered services, and agentic applications. * Design CI/CD pipelines for training, packaging, testing, release, rollback, and controlled promotion. * Containerise and deploy AI services using Kubernetes, serverless, or managed container patterns. * Build production\-grade agentic workflows using LangGraph and similar frameworks, including tool calling, state management, orchestration, and failure recovery. * Implement observability for models and agents, including latency, reliability, cost, token usage, tracing, drift, and quality signals. * Integrate AI services with product APIs, enterprise systems, security controls, and operational workflows. * Support model registry, experiment tracking, versioning, reproducibility, and lifecycle governance. * Define reusable engineering patterns for retrieval, memory, model routing, human\-in\-the\-loop intervention, and agent execution. * Optimise systems for reliability, scalability, cost, and operational simplicity. **What we are looking for** --------------------------- * Strong hands\-on experience in MLOps, platform engineering, or production AI infrastructure. * A solid understanding of cloud\-native software delivery. * Experience with Docker, Kubernetes, CI/CD, GitHub Actions, Terraform, or similar infrastructure\-as\-code approaches. * Experience with MLflow, model versioning, deployment pipelines, and runtime monitoring. * Experience deploying LLM or GenAI workloads into production, not just building prototypes. * Practical experience with agent frameworks such as LangGraph, LangChain, AutoGen, CrewAI, or similar. * Strong problem\-solving skills and the ability to work through production constraints. **Ideal Candidate Should Have** ------------------------------- * Experience with Azure AI Foundry, Azure OpenAI, Azure Container Apps, and Azure AI Search. * Experience with Databricks, feature engineering platforms, model serving, and data platform integration. * Familiarity with MCP, tool registries, and enterprise connector patterns. * Experience with vector databases, semantic retrieval, and retrieval\-augmented generation operating patterns. * Experience in banking, payments, lending, or other regulated environments. * Experience with policy enforcement, audit logging, model risk controls, and environment separation. **Example technologies** ------------------------ Azure AI Foundry, Databricks, MLflow, LangGraph, Python, Docker, Kubernetes, Azure Container Apps, AKS, Azure Functions, Azure Monitor, Application Insights, Azure AI Search, GitHub Actions, Terraform, vector stores. We are proud to offer a range of incentives to our employees worldwide. These benefits are available to everyone, regardless of grade, and reflect the values we stand for: **Flexibility:** Enjoy unlimited vacation, subject to local regulations and business priorities. Benefit from hybrid working arrangements and inclusive policies such as paid time off for voting, bereavement, and sick leave. **Well‑being:** Access confidential one‑to‑one support through our Employee Assistance Program, connect with our network of Wellbeing Champions and Gather Groups, and take part in monthly events and initiatives designed to help you thrive—inside and outside of work. **Health \& Financial Security:** Medical, life and disability insurance, retirement plans, lifestyle, and other benefits.\* **Sustainability:** Paid time off for volunteering and donation‑matching opportunities to support causes that matter to you. **Inclusion:** Get involved in our inclusion communities, such as Count Me In, Culture@Finastra, Proud@Finastra, Disabilities@Finastra, and Women@Finastra—open to everyone who wants to participate and contribute. **Career Development:** Access online learning and accredited courses through our Skills \& Career Navigator tool. **Recognition:** Take part in our global recognition program, Finastra Celebrates, and share your voice through regular employee surveys that help shape our culture and ways of working. * Specific benefits may vary by location. At Finastra, each individual is unique—bringing their own ideas, perspectives, cultural backgrounds, and experiences. We learn from one another, value what makes us different, and create an environment where everyone feels included, supported, and able to be their authentic selves. Be unique. Be exceptional. Help us make a difference at Finastra.


